1. Field of the Invention
The present invention generally relates to video analysis, and more particularly to analyzing and learning behavior based on streaming video data.
2. Description of the Related Art
Some currently available video surveillance systems have simple recognition capabilities. However, many such surveillance systems require advance knowledge (before a system has been developed) of the actions and/or objects the systems have to be able to seek out. Underlying application code directed to specific “abnormal” behaviors must be developed to make these surveillance systems operable and sufficiently functional. In other words, unless the underlying code includes descriptions of certain behaviors, the system will be incapable of recognizing such behaviors. Further, for distinct behaviors, separate software products often need to be developed. This makes the surveillance systems with recognition capabilities labor intensive and prohibitively costly. For example, monitoring airport entrances for lurking criminals and identifying swimmers who are not moving in a pool are two distinct situations, and therefore may require developing two distinct software products having their respective “abnormal” behaviors pre-coded.
The surveillance systems may also be designed to memorize normal scenes and generate an alarm whenever what is considered normal changes. However, these types of surveillance systems must be pre-programmed to know how much change is abnormal. Further, such systems cannot accurately characterize what has actually occurred. Rather, these systems determine that something previously considered “normal” has changed. Thus, products developed in such a manner are configured to detect only a limited range of predefined types of behaviors.